A C++ implementation of a neural network and Proximal Policy Optimization.

PPO (Proximal Policy Optimization) agent for training on Atari environments using C++ with libtorch, integrated with the Arcade Learning Environment (ALE) and built using Bazel.

DDNet Neural Network

testing MLP, DQN, PPO, SAC, policy-gradient by snakeAI

A C++20 framework for training autonomous drone flight controllers using deep reinforcement learning. Combines PPO optimization with a high-performance gRPC bridge to Microsoft AirSim for real-time quadrotor simulation and monitoring.

RLOP: A Framework for Reinforcement Learning, Optimization and Planning Algorithms

Trains a deep reinforcement learning agent in simulation testbed environments with the DRLA library.

Trains deep reinforcement learning agents in Atari environments via the DRLA library.

C++ Deep Reinforcement Learning Agent library

💻 PPO | BMSTU | IU7 | 6 sem

Reinforcement learning for flight simulation

TorchRL is a C++ reinforcement library using PyTorch C++ backend LibTorch

RL training for quadruped robot(mit minicheetah) various gaits in different velocity based on MPC controller.

A parallel reinforcement learning framework written in C++

Reinforcement Learning in Flashlight and Arrayfire

A Study on Reinforcement Learning in Starcraft Game Platform as a Collaborative Researcher of Samsung Company.

PyTorch C++ Reinforcement Learning

PPO implementation by using Pytorch C++ API

Implement some of the core deep RL algorithms with C++